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Interpreting function and fitness effects in diverse plant genomes requires transferable models. Language models (LMs) pretrained on large-scale biological sequences can capture evolutionary conservation and offer cross-species prediction better than supervised models through fine-tuning limited labeled data. We introduce PlantCaduceus, a plant DNA LM that learns evolutionary conservation patterns in 16 angiosperm genomes by modeling both DNA strands simultaneously. When fine-tuned on a small set of labeledArabidopsisdata for tasks such as predicting translation initiation/termination sites and splice donor/acceptor sites, PlantCaduceus demonstrated remarkable transferability to maize, which diverged 160 Mya. The model outperformed the best existing DNA language model by 1.45-fold in maize splice donor prediction and 7.23-fold in maize translation initiation site prediction. In variant effect prediction, PlantCaduceus showed performance comparative to state-of-the-art protein LMs. Mutations predicted to be deleterious by PlantCaduceus showed threefold lower average minor allele frequencies compared to those identified by multiple sequence alignment-based methods. Additionally, PlantCaduceus successfully identifies well-known causal variants in bothArabidopsisand maize. Overall, PlantCaduceus is a versatile DNA LM that can accelerate plant genomics and crop breeding applications. 

Social service providers play a vital role in the developmental outcomes of underprivileged youth as they transition into adulthood. Educators, mental health professionals, juvenile justice officers, and child welfare caseworkers often have first-hand knowledge of the trials uniquely faced by these vulnerable youth and are charged with mitigating harmful risks, such as mental health challenges, child abuse, drug use, and sex trafficking. Yet, less is known about whether or how social service providers assess and mitigate the online risk experiences of youth under their care. Therefore, as part of the National Science Foundation (NSF) I-Corps program, we conducted interviews with 37 social service providers (SSPs) who work with underprivileged youth to determine what (if any) online risks are most concerning to them given their role in youth protection, how they assess or become aware of these online risk experiences, and whether they see value in the possibility of using artificial intelligence (AI) as a potential solution for online risk detection. Overall, online sexual risks (e.g., sexual grooming and abuse) and cyberbullying were the most salient concern across all social service domains, especially when these experiences crossed the boundary between the digital and the physical worlds. Yet, SSPs had to rely heavily on youth self-reports to know whether and when online risks occurred, which required building a trusting relationship with youth; otherwise, SSPs became aware only after a formal investigation had been launched. Therefore, most SSPs found value in the potential for using AI as an early detection system and to monitor youth, but they were concerned that such a solution would not be feasible due to a lack of resources to adequately respond to online incidences, access to the necessary digital trace data (e.g., social media), context, and concerns about violating the trust relationships they built with youth. Thus, such automated risk detection systems should be designed and deployed with caution, as their implementation could cause youth to mistrust adults, thereby limiting the receipt of necessary guidance and support. We add to the bodies of research on adolescent online safety and the benefits and challenges of leveraging algorithmic systems in the public sector. 

Researchers continue to explore ways to understand and promote pro-environmental behavior (PEB) amongst various populations. Despite this shared goal, much debate exists on the operationalization and the dimensionality of PEB and how it is measured. This piecemeal approach to measurement has limited the ability to draw conclusions across studies. We address limitations associated with previous measures of PEB by developing a multi-dimensional scale that is validated across both a general population of individuals residing in the United States as well as a group of individuals associated with a pro-environmental organization. Exploratory and confirmatory factor analyses and reliability estimation were conducted for the developed measure across these two populations. Measurement invariance testing was also utilized to assess the psychometric stability of the scale across the two groups. Results indicated an 11 item scale was best fitting with two sub-scales: private and public behaviors. Implications for research and practice are discussed. 

The ability to identify and track T-cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile TCR repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data are limited compared with RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across 4 cancer cohorts including both T-cell-rich and T-cell-poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as provide relative frequencies of clonotypes in T-cell-rich tissues and low-diversity repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T-cell-poor tissues, especially in highly diverse repertoires of T-cell-poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate RNA-Seq into the immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq. 

Abstract Ticks are vectors of many diseases and are expanding in geographic distribution. However, how ticks will fare in their new environments, where they may experience stressful climatic conditions at the expansion front, remains unclear. Since there is a trade‐off in ticks between behaviors that promote longevity and behaviors that promote reproduction, we hypothesized that extreme climatic stress reduces the survivorship of ticks but increases the frequency of tick host‐seeking behavior, or questing. Here, we used a novel method to simulate climatic stress on individual ticks of three species—Amblyomma americanum,Dermacentor variabilis, andIxodes scapularis—to evaluate their survival, physiology, and questing behavior. The first experiment involved placing 144 adult ticks of each species in two temperature ranges (15–25°C and 25–35°C) and three relative humidity (RH) treatments (32%, 58%, and 84% RH). We assessed the ticks daily for survivorship and questing, and we measured water loss by comparing the mass of each tick when it died to when it was fully hydrated. In this first experiment, ticks in warmer and less humid conditions generally died faster than those in cooler and more humid conditions. Ticks of all three species were more likely to quest shortly before their death and consistently died after losing approximately 50%–56% of their total body water content, butIxodesreached that threshold much faster than the other two species. The second experiment involved placing 18 ticks of each species at 35°C and 32% RH. We assessed the ticks every 3 h for survivorship, questing, and water loss. Ticks again were more likely to quest shortly before their death. With frequent checks, we were able to measure the dehydration tolerance more accurately and the rate of water loss. Ticks of all three species consistently died after losing approximately 51% of their total body water content. However,Ixodeslost water approximately 5 times faster thanAmblyommaand 11 times faster thanDermacentor. These results demonstrate that severe climatic stress tilts the trade‐off toward higher questing rates but not higher overall questing time because of reduced survival rates.